Efficacy of anti-PD1/PD-L1 immunotherapy in non–small cell lung cancer is dependent upon Immunoscore IC CD8 and PD-L1 status.
Authors: Jerome Galon, Frederic Bibeau, Laurent Greillier, Jean David Fumet, Alis Ilie, Florence Monville, Caroline Laugé, Aurelie Catteau, Isabelle Boquet, Amine Majdi, Youssef Oulkhouir, Nicolas Brandone, Julien Adam, Thomas Sbarrato, Alboukadel Kassambara, Jacques Fieschi, Stephane Garcia, Anne Laure Lepage, Pascale Tomasini, François Ghiringhelli
Journal: Journal of Clinical Oncology (2022)

2509 Background: Anti-PD1 and PD-L1 antibodies (mAb) are immune checkpoint inhibitors (ICIs) to treat patients with metastatic non–small cell lung cancer (NSCLC). Unfortunately, only a handful of patients respond to ICIs. Methods: A cohort of patients with metastatic NSCLC (n=133) treated with anti-PD1 or anti-PD-L1 mAb in two independent care centers was evaluated. An independent cohort of 132 patients from another hospital was used as a validation. Immunoscore IC, an in vitro diagnostic test (CE-IVD), was used on a routine single FFPE slide, and duplex immunohistochemistry CD8 and PD-L1 staining was quantified using digital pathology. Quantitative and spatial parameters related to cell location, number, proximity, and clustering were analyzed. An Immunoscore IC–based model discriminated patients into 2 categories or 3 categories. Results: Anti–PD-L1 clone (HDX3) had similar characteristics as other anti–PD-L1 clones (22C3, SP263) with a mean overall agreement above 95%. Intra- and inter-laboratory concordances for classifying patients at 1% cut-off according to digital anti–PD-L1 (HDX3) were 100% and 94%, respectively. Routine laboratory evaluation of PD-L1 expression showed an agreement with digital anti–PD-L1 quantification of 92% and 97% at 1% and 50% cut-offs, respectively. Using univariate Cox model after FDR correction, 5 pathological dichotomized variables were significantly associated with PFS (all p &lt; 0.0001). These variables included: CD8 free of PD-L1, CD8 clusters, CD8 cells in proximity of PD-L1 cells, CD8 number, PD-L1 cells in proximity of CD8 cells. Similar results were found using univariate Cox analysis on continuous variables (all p &lt; 0.003) in two independent cohorts of patients. Using multivariate Cox model Immunoscore IC classification improved the discriminating power of prognostic model, which included clinical variables and pathologist PD-L1 assessment. In two categories, the Immunoscore IC risk score was significantly associated with both patients’ PFS (p &lt; 0.0001) and OS (p &lt; 0.0001) in the training cohort and in the validation cohort (PFS: p = 0.0047, OS: p &lt; 0.0001). Further increased hazard ratios were found when stratifying patients into 3 categories of Immunoscore IC. At 6 months, PFS rates were 10% versus 60% in the training cohort and 20% versus 62% in the validation cohort for high-risk and low-risk Immunoscore IC score, respectively. All patients (100%) with high-risk Immunoscore IC score relapsed in less than 18 months, in contrast to 34% and 33% of low-risk Immunoscore IC patients who did not relapse for more than 36 months in the training and validation cohorts, respectively. Conclusions: These data underline that Immunoscore IC is a potent tool to predict the efficacy of ICIs in patients with NSCLC. Immunoscore IC characterized patients who are resistant to ICIs.